Role of Bone Marrow Biopsy in the Staging of Diffuse Large B-Cell Lymphoma in the PET/CT Era
Notice bibliographique
Résumé
Abstract Background Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma (NHL) and bone marrow involvement by lymphoma is seen in up to one third of cases, as assessed by iliac crest bone marrow biopsy (BMB) at the time of diagnosis. Traditionally, BMB has been the gold standard test to detect bone marrow infiltration by lymphoma. 18-Fluoro-deoxyglucose positron emission tomography combined with computed tomography (PET/CT), has become standard in the initial staging of DLBCL. Prior studies have suggested that PET/CT staging may obviate the need for staging BMB in patients with Hodgkin lymphoma. However, because of limited evidence, this approach has not been adopted in patients with DLBCL. We investigated whether BMB adds useful information to PET/CT staging in patients with an initial diagnosis of DLBCL. Patients and Methods Patients with a new diagnosis of DLBCL who underwent both staging PET/CT and BMB were retrospectively identified across three institutions: British Columbia Cancer Agency (n=149, 2011-2013), Aalborg University Hospital (n=179, 2007-2013), and Copenhagen University Hospital (n=202, 2009-2012). We reviewed the reports of PET/CT scans and BMBs from each academic institution performed at the time of diagnosis prior to treatment of DLBCL. Ann Arbor stage was determined including PET/CT with and without the contribution of BMB, and the proportion of stage IV cases by each method was calculated. Results 530 patients were identified: median age 65 years (range 16-90), 294 (56%) male, 137 (26%) largest mass >10cm, 263 (50%) elevated LDH, 105 (20%) performance status >2, and 149 (28%) with more than one extranodal site. International Prognostic Index score was 0-1 in 159 (30%), 2 in 145 (27%), 3 in 119 (23%), and 4-5 in 107 (20%) patients. 520 (98%) received rituximab-containing chemotherapy, 130 (25%) radiotherapy, and 3 (<1%) consolidative autologous stem cell transplantation. A total of 181 (34%) patients had bone marrow involvement established by either PET/CT (n=146, 28%), BMB (n=87, 16%), or both (n=52, 10%). Focal skeletal lesions on PET/CT were unifocal (n=42), bifocal (n=15), multifocal/diffuse (n=89). 52 of the 146 patients (36%) with positive PET/CT had a positive BMB (39 DLBCL, 13 iNHL), while 35 of the 384 patients (9%) with negative PET/CT had a positive BMB (12 DLBCL, 23 iNHL). Table 1 shows the distribution of Ann Arbor staging as defined by PET/CT alone and with inclusion of BMB results. BMB upstaged 12/209 (6%) stage I/II patients to stage IV, including 3 patients with DLBCL and 9 patients with iNHL in the bone marrow. Focal skeletal lesions on PET/CT identified bone marrow involvement by lymphoma (DLBCL or iNHL) with sensitivity 60%, specificity 79%, positive predictive value 36%, and negative predictive value 91%. In a subgroup analysis excluding the 36 patients with iNHL in the bone marrow, focal skeletal lesions on PET/CT identified bone marrow involvement by DLBCL with sensitivity 78%, specificity 79%, positive predictive value 29%, and negative predictive value 97%. Conclusions In patients with DLBCL, staging PET/CT does not identify all cases with bone marrow involvement. BMB upstaged 6% of patients with stage I/II who had a PET/CT negative for any skeletal involvement. However, the majority had indolent histologies in the bone marrow, and only 1% were upstaged due to involvement of the bone marrow with DLBCL. Although PET/CT has a high negative predictive value for ruling out bone marrow involvement by high grade lymphoma, BMB remains a necessary component in the evaluation of patients with a new diagnosis of DLBCL mainly because of its ability to detect iNHL that was missed by PET/CT which may have implications in the post-treatment surveillance setting. Table 1. Clinical staging by PET/CT alone and with inclusion of bone marrow biopsy results. Clinical Stage Staging Modality Patients upstaged to stage IV by bone marrow biopsy PET/CT alone PET/CT and bone marrow biopsy N (%) N (%) N I 121 (23) 114 (21) 7 (2 DLBCL, 5 iNHL) II 88 (17) 83 (16) 5 (1 DLBCL, 4 iNHL) III 92 (17) 77 (15) 15 (5 DLBCL, 10 iNHL) IV 229 (43) 256 (48) Not applicable Disclosures No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».